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Statistics - Univariate Statistics and Methodology using R - Report Writing Assignment Help

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Highlights

Internal Code: 1ABBIF

Statistics Report Writing Assignment Help

Task: You are given four separate data sets:
  • df_e is a data set of 520 pictures and their associated variables in a English language picture naming study
  • df_c, df_h, and df_s are data sets of 173 pictures in a Chinese, Hungarian, and Spanish language picture naming study, respectively. Each data set uses a different picture set.
The code book for the data sets can be found on LEARN.  Questions Question 1 Is there a relationship between the frequency of a target word in the English corpus and reaction time (RT) on a picture-naming task? Once you are content that the data are appropriately cleaned, run the following model: m1 <- lm(rttar ~ lnfreq, data = df_e) Question 1.1 Concisely report and interpret the results of the model. Question 1.2 What is the predicted RT for a word with a frequency of 20? Hint: Don’t forget the the frequency variable is log-transformed (see codebook for details) and that, in R, exp() is the inverse function of log(). Question 1.3 Produce and interpret a diagnostic plot of the model that shows whether or not the model residuals are normally distributed. Question 2 Do target word length and the number of synonyms a word has have additional effects on RT above and beyond that of word frequency in the English language data set? Question 2.1 Fit an appropriate model to test this question. Question 2.2 Run model diagnostics and, if needed, re-fit the model. Question 2.3 Report and interpret the results of the final model. Question 3 Do variables entered as predictors in the Question 2 model predict whether or not at least one par- ticipant will produce an error response on a picture naming task in the English language data set? Pictures for which there are any invalid or incorrect responses should be coded as containing errors. Question 3.1 Fit, report, and interpret an appropriate model to test this question. Question 3.2 What is the predicted probability of a correct response on a picture whose name has a frequency of 12, is 3 syllables long and has only one form? Question 4 Does the effect of target word frequency on RT vary significantly between Chinese, Hungarian, and Spanish? Hint: You will need to construct a single data frame to answer this question. Question 4.1 Fit an appropriate model to test this question. Run model diagnostics and re-fit the model if needed. Question 4.2 Report and interpret the results of the final model. Question 4.3 Which language has the weakest effect of frequency on RT? Describe it in terms of unit change in RT as a result in a unit change in log-frequency. Remember:
  • Explore and describe the data.
  • Build appropriate models, evaluate them and their associated assumptions, and interpret the results.
  • Let your models be informed by the research questions they are supposed to address. There is seldom a need for mind-bogglingly complex and borderline uninterpretable 6-way interaction models.
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